The one-shot similarity kernel

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 897-902

  Wolf, Lior ^a   Hassner, Tal ^b   Taigman, Yaniv ^c  

^a TEL AVIV UNIVERSITY   (Israel)

^b OPEN UNIVERSITY OF ISRAEL   (Israel)

^c Facecom   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

DESCRIPTORS; IMAGE REPRESENTATIONS; KERNEL-METHODS; MULTI-CLASS; POSITIVE DEFINITE KERNELS; SHOT SIMILARITY; UNDERLYING MECHANISM;

COMPUTER VISION;

FACE RECOGNITION;

EID: 77953190446     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459323     Document Type: Conference Paper

References (35)

1. E. Bart and S. Ullman. Cross-generalization: learning novel classes from a single example by feature replacement. In CVPR, 2005.
2. S. Belongie, J. Malik, and J. Puzicha. Shape context: A new descriptor for shape matching and object recognition. In NIPS, 2001.
3. M. Bilenko, S. Basu, and R. Mooney. Integrating constraints and metric learning in semi-supervised clustering. In ICML, 2004.
4. S. Boughorbel, J.-P. Tarel, and N. Boujemaa. Conditionally positive definite kernels for svm based image recognition. In ICME, 2005.
5. C.Berg, J. Christensen, and P.Ressel. Harmonic analysis on semigroups. Theory of positive definite and related functions. Springer- Velarg, New-York, 1994.
6. C. Cortes and V. Vapnik. Support-vector networks. Machine Learning, 20(3):273-297, 1995.
7. N. Cristianini, J. Kandola, A. Elisseeff, and J. Shawe-Taylor. On kernel-target alignment. In NIPS, 2002.
8. R. O. Duda, P. E. Hart, and D. G. Stork. Pattern classification, second edition. Wiley, 2001.
9. L. Fei-Fei, R. Fergus, and P. Perona. One-shot learning of object categories. PAMI, 28(4):594-611, 2006.
10. M. Fink. Object classification from a single example utilizing class relevance pseudo-metrics. In NIPS, 2004.
11. R. Fisher. The use of multiple measurements in taxonomic problems. Annals Eugenics, 7:179-188, 1936.
12. P. Geurts, D.Ernst, and L. Wehenkel. Extremely randomized trees. Machine Learning, 36(1):3-42, 2006.
13. T. Hastie, , R. Tibshirani, and J. Friedman. The elements of statistical learning. Springer, 2001.
14. T. Hertz, A. Bar-Hillel, and D. Weinshall. Boosting margin based distance functions for clustering. In ICML, 2004.
15. D. Hoiem, A. Efros, and M. Hebert. Geometric context from a single image. In ICCV, 2005.
16. G. Huang, M. Jones, and E. Learned-Miller. Lfw results using a combined nowak plus merl recognizer. In Faces in Real-Life Images Workshop in ECCV, 2008.
17. C. image collection. Website. http://calphotos.berkeley.edu/.
18. M. B. insect photo collection. Website. http://bscit.berkeley.edu/ biocode/.
19. H. Jegou, M. Douze, and C. Schmid. Hamming embedding and weak geometry consistency for large scale image search. In ECCV, 2008.
20. M. Jones and P.Viola. Face recognition using boosted local features, 2003.
21. W. Krzanowski, P. Jonathan, W. McCarthy, and M. Thomas. Discriminant analysis with singular covariance matrices: methods and applications to spectroscopic data. Applied statistics, 41:101-115, 1995.
22. D. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91-110, 2004.
23. S. Mika, G. Rätsch, J. Weston, B. Schölkopf, and K. Müler. Fisher discriminant analysis with kernels. In IEEE Workshop on Neural Networks for Signal Processing, 1999.
24. E. Nowak and F. Jurie. Learning visual similarity measures for comparing never seen objects. In IEEE Conference on Computer Vision and Pattern Recognition, June 2007.
25. T. Ojala, M. Pietikainen, and D. Harwood. A comparative-study of texture measures with classification based on feature distributions. Pattern Recognition, 29(1):51-59, 1996. (Pubitemid 126402562)
26. T. Ojala, M. Pietikäinen, and T. Mäenpää. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. PAMI, 24(7):971-987, 2002.
27. B. Scholkopf. The kernel trick for distances. In NIPS, 2000.
28. B. Scholkopf and A. J. Smola. Learning with Kernels. MIT Press, Cambridge, MA, USA, 2001.
29. N. Shental, T. Hertz, D. Weinshall, and M. Pavel. Adjustment learning and relevant component analysis. In ECCV, 2002.
30. J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In ICCV, 2003.
31. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.
32. K. Weinberger, J. Blitzer, and L. Saul. Distance metric learning for large margin nearest neighbor classification. NIPS, 2006.
33. L. Wolf, T. Hassner, and Y. Taigman. Descriptor based methods in the wild. In Faces in Real-Life Images Workshop in ECCV, 2008.
34. E. Xing, A. Y. Ng, M. Jordan, and S. Russell. Distance metric learning, with application to clustering with side-information. In NIPS, 2003.
35. H. Zhang, A. Berg, M. Maire, and J. Malik. Svm-knn: Discriminative nearest neighbor classification for visual category recognition. In CVPR, 2006.